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Found 2 papers, 1 papers with code
SPOT: Knowledge-Enhanced Language Representations for Information Extraction
To address these problems, we propose a new pre-trained model that learns representations of both entities and relationships from token spans and span pairs in the text respectively.
Ranked #4 on
Relation Extraction
on SemEval-2010 Task-8
Abstractified Multi-instance Learning (AMIL) for Biomedical Relation Extraction
In this work, we propose a novel reformulation of MIL for biomedical relation extraction that abstractifies biomedical entities into their corresponding semantic types.
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